Twitter Analytics

Twitter Analytics A user’s guide to interpreting, reinterpreting and misinterpreting the social media service. Dr Stephen Dann School of Management Marketing & International Business, Australian National University @stephendann or stephen.dann@anu.edu.au

If you’re on Twitter Questions can be sent to @stephendann

Twitter.

Twitter matters because of what it is: at its heart, a platform that offers an exchange of ideas and information on an unprecedented scale.

Why Twitter Matters : Marketing : Idea Hub :: American Express OPEN Forum http://www.openforum.com/idea-hub/topics/marketing/article/why-twitter-matters-ann-handley Fri Oct 02 2009 21:16:49 GMT+1000 (AUS Eastern Standard Time)

Twitter in Plain English

For those who came in late

Twitter.com

140 character message

Social network

Web2.0

End of the world as we know it

Best thing since sliced bread

Twitter! (What is it good for?)

health community (Berger 2009)

public libraries (Cahill 2009, Cuddy 2009)

political campaigns (Cetina 2009, Henneburg et al 2009)

business (Dudley 2009; Power and Forte 2008)

journalism (Ettama 2009)

civil unrest and protests (Fahmi 2009)

social activism (Galer-Unti 2009)

live coverage of events (Gay et al 2009)

eyewitness accounts (Lariscy et al 2009)

government (Macintosh 2009)

education (Parslow 2009).

Uses and usage

casual listening platform (Crawford 2009),

creating the illusion of physicality (Hohl 2009)

sense of connectedness and relationship (Henneburg et al 2009)

venue for conversation (Steiner 2009)

How to dissect a living medium?

Raw Counts Tweetstats – www.tweetstats.com

Text Analysis Tweetstats – www.tweetstats.com Wordle – wordle.com

Leximancer Leximancer – www.leximancer.com

Coded Content Analysis Made up for this set of slides.

Same Data set… So many different ways to present the results

Coded Content Analysis

Social awareness streams

Three factors

the public (or personal-public) nature of the communication and conversation

the brevity of posted content

highly connected social space / articulated online contact networks.

Naaman, Boase, and Lai (2010),

infolab.stanford.edu/~mor/research/naamanCSCW10.pdf

Prior Analysis

Analysis 1: Take the people out

Krishnamurthy et al (2008)

users were classified by

follower/following counts,

Numbers and ratios

means and mechanisms of their engagement

Web (61.7%), mobile/text (7.5%), software (22.4%)

volume of use

Tweets per time period

Analysis 2: Content Category

Java et al 2007

1,348,543 tweets

76,177 users

April 01, to May 30, 2007

Four meta-categories

daily chatter

conversations

information / URL sharing

news reporting

Analysis 3: Insider Coding

Jansen et al (2009)

tweets with brand name

expression of brand sentiment

13-week period

April 4, 2008 to July 3, 2008.

650 reporting episodes

13 x 50 brands

149,472 tweets

Sentiment Scale

No Sentiment

Wretched

Bad

So-so

Swell

Great

Content Schema

Sentiment

Information seeking

Information providing

Comment

Analysis 4: Pear’s Babble

Pear Analytics (2009)

2000 tweets

11am to 5pm

10 working days

Six part classification

news (3.6%),

spam (3.75%),

self-promotion (5.85%),

pointless babble (40.55%)

conversational (37.55%)

pass-along value (8.70%).

Analysis 5: Where’s the party @?

Honeycutt and Herring (2009)

four one-hour samples

four-hour intervals

6 a.m. to 6 p.m. Eastern Standard Time, on January 11, 2008

Sample of 200 tweets coded with grounded methodology

1) Addressivity: Directs a message to another person

2) Reference: Makes reference to another person, but

does not direct a message to him or her.

3) Emoticon: Used as part of an emoticon.

4) Email: Used as part of an email address.

5) Locational 'at': Signals where an entity is located.

6) Non-locational 'at': Used to represent the preposition 'at' other than in the sense of location.

7) Other: Uses not fitting into any other category,

Analysis 6: Rigor and Bass

Naaman, Boase and Lai (2010)

Sample of 400 tweets

more than one category was assigned to a single message.

Sampling frame

125,593 unique user IDs

‘ personal’ Twitter users

10 friends, 10 followers, 10 messages

911 users

N = 350 users

The Categories

Information Sharing

Self Promotion

Opinions/Complaints

Statements and Random Thoughts

Me now

Question to followers

Presence Maintenance

Anecdote (me)

Anecdote (others)

The consistent theme

People keep using Twitter for personal use.

Discussions of “self”

Pointless babble

Conversational

All criticisms of the use of twitter for pleasure and personal consumption

What Twitter looks like…

… and how are people using Twitter?

Twitter – www.twitter.com

Recoding the Platform Let’s do it my way

Theory and Ideology

Useful versus Enjoyable

Bohme (2006) outlines a propensity of society to classify technology of all forms into

“ useful and therefore valuable”

“ enjoyable, therefore irrelevant”.

Böhme, G (2006) Technical Gadgetry: Technological Development in the Aesthetic Economy, Thesis Eleven, 86 (1): 54-66

Method

Grounded Theory

Broad categories based on / supported by six prior studies

Sub categories developed from theory and data

Sample

Personal Twitter History

@stephendann (274 Following / 355 Followers)

2841 messages

Mar 13 2007 to Aug 18 2009

@darthvader (5,513 Following / 113,624 Followers)

484 messages

Jan 09 2007 to Sep 27 2009

Sample

@stephendann

274 Following / 355 Followers

Supports Krishnamurthy et al (2008) 250 follower rule

2841 tweets

Start: Tue Mar 13 2007 11:53:01

End: Tue Aug 18 2009 07:29:30

Data was captured from the timeline using the Sujathan (2009) “ Twitter to pdf ” software.

Categories and Results

Major Categories

Conversational

Uses an @statement to address another user

Status

An answer to “What are you doing now?”.

Pass along

Tweets of endorsement of content

News

Identifiable news content which is not UGC

Phatic

Content independent connected presence

Spam

Junk traffic, unsolicited automated posts, and other automated tweets generated without user consent

Results- @stephendann phatic

Minor Categories

Conversational

1. Query

2. Referral

3. Action

4. Response

Status

1. Personal

2. Temporal

3. Location

4. Mechanical

5. Physical

6. Work

7. Activity

Pass along

1. RT

2. UGC

3. Endorsement

News

1. Headlines

2. Sport

3. Event

4. Weather

Phatic

1. Greeting

2. Fourth wall

3. Broadcast

4. Unclassifiable

Spam

Results - @stephendann

Conversational

Query

Questions, question marks or polls

Referral

An @response which contains URLs or recommendation of other Twitter users.

Action

Activities involving other Twitter users

Response

Catch-all classification for conversation @tweets

Conversational @USERNAME Beware the polar bears. 30% 850 Response Invading Germany from France. Who's with me? 17% 480 Query @USERNAME Items under $1000 are exempt. http://is.gd/AV7K 2% 66 Pass-along *waves at @USERNAME* 3% 77 Action Exemplar % N Category 3rd pers plural 73.84 21.97 17.05 13637 30% 850 Response Impersonal pronouns, Auxiliary verbs, Tentative, Discrepancy, QMark 75.33 21.22 10.13 7032 17% 480 Query OtherP, Period 54.31 21.86 18.89 1020 2% 66 Pass-along Conjunctions, Inhibition, Inclusive Biological processes 67.75 23.80 14.74 958 3% 77 Action Linguistic Inquiry Results Dictionary Words >6 letters Words/ Sentence Word Count % N Category

Conversational

Status (1 of 2)

Personal

Positive or negative sentiment in the form of personal opinion or emotional status

Temporal

References to specific dates, times, statements of temporal nature (waiting) and temporal action (“Time to” )

Location

Geographic references and location statements, including statements of traveling, location change

Status (2 of 2)

Mechanical

Technology or mechanical systems

Physical

Sensory experiences of a physical nature

Work

Reference to work related activity

Activity

Direct statements that answer “What are you doing now?”

Status Firing off e-mail after e-mail to clear my to do list (knowing that's a great way to regenerate to do list items doesn't stop me or help me) 7% 196 work Waiting for my 2pm performance review to start. 6% 170 temporal It's freezing out there this morning 1% 37 physical I liked Modest Mouse after they became famous. 8% 221 personal Well... I'm in trouble. Used 3829.060MB (62.322%) of your 6GB. You have 22 days remaining 4% 106 mechanical Standing in a lecture theatre talking about Marketing Management. 2% 69 location Diplomacy is the art of saying "Nice doggy" until you find a big enough rock. Captaincy is the timely provision of large enough rocks. 5% 140 broadcast Playing with the internet in the name of science 1% 35 activity Work 80.19 23.96 16.59 3881 7% 196 work Prepositions 79.05 19.84 14.11 3160 6% 170 temporal Perceptual processes, feel, body, health 81.91 23.10 16.87 658 1% 37 physical Total function words, Common verbs, Past / Present tense, Adverbs, Cognitive processes, 80.71 19.05 19.35 4121 8% 221 personal Sadness 70.43 22.02 13.88 1985 4% 106 mechanical Articles, space 78.12 22.96 12.67 1115 2% 69 location Friends, Quote 71.21 22.84 11.21 2119 5% 140 broadcast see, Ingestion,Achievement 76.17 23.26 14.41 533 1% 35 activity Linguistic Inquiry Results Dictionary Words >6 letters Words/ Sentence Word Count % N Category

Status

Pass along

RT

Any statement reproducing another Twitter status using the via @ or RT protocol

UGC

Links to content created by the user

Endorsement

Links to web content not created by the sender

Pass Along http://twitpic.com/2o1c1 - Bus Slogan Generator Time - http://is.gd/hU2Q 4% 122 Ugc L4D Survivors in Rockband2 singing L7 Pretend We're Dead. http://is.gd/BsVE (HT to @LesbianGamers ). It's seriously amazing. 2% 48 RT I'm looking myself up on Publish or Perish (http://rurl.org/iw4) to find a reference to a paper that cited me because I want to cite them 4% 108 endorsement Pass along Exemplar % N Category Numbers, leisure 52.89 20.61 39.98 1679 4% 122 Ugc SemiC 54.31 24.75 16.85 893 2% 48 RT Parenth, Dash 55.71 21.05 30.12 1777 4% 108 endorsement Linguistic Inquiry Results Dictionary Words >6 letters Words/ Sentence Word Count % N Category

Pass Along

News

Headlines

Coverage of breaking news and personal eye-witness accounts of news events

Sport

Identifiable results of sporting events

Event

Any tweet which represents the live discussion of an identified or identifiable event

Weather

Report of weather conditions without commentary

News - - - Headlines - - - Sport Between NASA's satellite and autoanalysis of imagery, and Google Map data, scientific proof where there's smoke, there's fires #bcc2 0% 13 Event News Exemplar % N Category Negative emotion, Anger Certainty Perceptual processes 65.62 22.92 10.67 192 0% 13 Event News Linguistic Inquiry Results Dictionary Words >6 letters Words/ Sentence Word Count % N Category

Phatic

Greeting

Statements of greetings to the broader Twitter community

Fourth wall

Textual equivalent of comments made directly to camera in television or cinema

Broadcast

Textual soliloquy, monologue and undirected statements of opinion

Unclassifiable

Unclassifiable strings of text

Phatic AAAAAAAAAAAAAAARGH 0% 7 Unclassifiable Good morning Twitterverse. How's the world outside? 1% 17 Greeting Note to self: Just because you're carrying tiny vials of hypercaffeine is no reason to start calculating remote delivery systems for them. 2% 49 Fourth wall *wanders through his twitter follower list, blocking all of the automated/spam follower accounts* 1% 30 Action Phatic Exemplar % N Category NIL 33.33 33.33 3.00 6 0% 7 Unclassifiable Future tense, Positive emotion Relativity, time 78.37 29.33 7.70 208 1% 17 Greeting Negations, Quantifiers, Social processes, Humans, Affective processes, Causation, Exclusive 76.44 20.69 12.29 836 2% 49 Fourthwall Anxiety, hear, motion 75.22 26.75 22.80 456 1% 30 Action Linguistic Inquiry Results Dictionary Words >6 letters Words/ Sentence Word Count % N Category

Phatic

Findings

Non commercial Twitter classification

Replicable across multiple accounts

Heavy duty lifting

Manual coding

Qualitative research

Implications

Twitter

Consumption analysis

Consumer framework

Not always a business framework

Future research The Public Timeline versus the Classification Scheme

Questions [email_address] Or @stephendann

References

Böhme, G (2006) Technical Gadgetry: Technological Development in the Aesthetic Economy, Thesis Eleven, 86 (1): 54-66

Cetina, K K 2009, What is a Pipe? bama and the Sociological Imagination, Theory, Culture & Society 2009 26(5): 129–140

Crawford, K (2009)'Following you: Disciplines of listening in social media',Continuum,23:4,525 — 535

Dudley, E 2009, Editorial: Lines of Communication, Journal of Librarianship and Information Science 2009; 41; 131-134

Ettama, J 2009 New media and new mechanisms of public accountability, Journalism 2009; 10; 319-321

Fahmi, W S 2009, Bloggers' street movement and the right to the city. (Re)claiming Cairo's real and virtual "spaces of freedom", Environment and Urbanization 2009; 21; 89-107

Galer-Unti, R 2009, Guerilla Advocacy: Using Aggressive Marketing Techniques for Health Policy Change, Health Promotion Practice, 10; 325-327

Gay, P Plait, P, Raddick, J, Cain, F and Lakdawalla, E (2009) "Live Casting: Bringing Astronomy to the Masses in Real Time", CAP Journal, June 26-29

Henneburg, S. Scammell, M and O'Shaughnessy, N (2009) Political marketing management and theories of democracy, Marketing Theory 2009; 9; 165-188

Honeycutt, C and Herring, S C (2009) Beyond Microblogging: Conversation and Collaboration via Twitter, (2009). Proceedings of the Forty-Second Hawai’i International Conference on System Sciences (HICSS-42). Los Alamitos, CA: IEEE Press. 1-10, http://ella.slis.indiana.edu/~herring/honeycutt.herring.2009.pdf

Jansen, B, Zhang, M, Sobel, K and Chowdury, A (2009) Twitter power: Tweets as electronic word of mouth, Journal of the American Society for Information Science and Technology, 60(11):2169–2188, 2009 http://ist.psu.edu/faculty_pages/jjansen/academic/jansen_twitter_electronic_word_of_mouth.pdf

Java, A, Song, X, Finin, T and Tseng, B (2007) Why We Twitter: Understanding Microblogging Usage and Communities, Joint 9th WEBKDD and 1st SNA-KDD Workshop ’07 , August 12, 2007, p 56-65

References

Krishnamurthy, B, Gill, P and Arlitt, M (2008) A Few Chirps About Twitter, WOSN'08, August 18, 2008, 19-24

Lariscy, R Avery, E J, Sweetser, K and Howes, P 2009 An examination of the role of online social media in journalists’ source mix, Public Relations Review 35 (2009) 314–316

Macintosh, A 2009, The emergence of digital governance, Significance, December, 176-178

Naaman, M, Boase, J and Lai, C-H (2010) Is it Really About Me? Message Content in Social Awareness Streams, CSCW 2010, February 6–10

Parslow, G, 2009, Commentary: Twitter for Educational Networking, BIOCHEMISTRY AND MOLECULAR BIOLOGY EDUCATION Vol. 37, No. 4, pp. 255–256, 2009

Pear Analytics (2009) Twitter Study – August 2009, http://www.pearanalytics.com/wp-content/uploads/2009/08/Twitter-Study-August-2009.pdf

Power, R and Forte, D 2008, War & Peace in Cyberspace: Don’t twitter away your organisation’s secrets, Computer Fraud and Security, August, 18-20

Zhao, D and Rosson, M B, How and Why People Twitter: The Role that Micro-blogging Plays in Informal Communication at Work, GROUP’04, May 10–13, 2009, 243-252

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